Molecular pathology is the examination at a molecular level of the DNA, mRNA, and proteins that cause or are otherwise associated with disease. Gene amplification and/or overexpression have been identified as an indicator of patient prognosis in a variety of tumors or for determining those patients that should be provided certain treatments. For example, a certain type of breast cancer is associated with an over-abundance (e.g., over expression) of the human epidermal growth factor 2 (“HER2”) versus the number of chromosome 17s found in the cell. Sadly, this alteration is also an independent prognostic factor predictive of poor clinical outcome and a high risk of recurrence. By detecting the number of HER2 genes versus the number of chromosome 17s in a tissue sample, this particular type of breast cancer can be more readily identified and treatment options can be evaluated.
In-situ hybridization can be used to look for the presence of a genetic abnormality or condition such as amplification of cancer causing genes specifically in cells that, when viewed under a microscope, morphologically appear to be malignant. In situ hybridization (ISH) employs labeled DNA or RNA probe molecules that are anti-sense to a target gene sequence or transcript to detect or localize targeted nucleic acid target genes within a cell or tissue sample. ISH is performed by exposing a cell or tissue sample immobilized on a glass slide to a labeled nucleic acid probe which is capable of specifically hybridizing to a given target gene in the cell or tissue sample. Several target genes can be simultaneously analyzed by exposing a cell or tissue sample to a plurality of nucleic acid probes that have been labeled with a plurality of different nucleic acid tags. By utilizing labels having different emission wavelengths, simultaneous multicolored analysis may be performed in a single step on a single target cell or tissue sample. For example, INFORM HER2 Dual ISH DNA Probe Cocktail Assay from Ventana Medical Systems, Inc., is intended to determine HER2 gene status by enumeration of the ratio of the HER2 gene to Chromosome 17. The HER2 and Chromosome 17 probes are detected using a two color chromogenic ISH in formalin-fixed, paraffin-embedded human breast cancer tissue specimens.
Digital microscopy systems have been introduced wherein tissue samples are prepared in a traditional manner, i.e. mounted on glass slides, but instead of having the pathologist view the samples using a manually controlled optical microscope, the slides are processed using digital imaging equipment. In recent years, digital pathology has transformed from the use of camera-equipped microscopes to high-throughput digital scanning of whole tissue samples. This development not only enables virtual storing and sharing of biological data, but it also improves the turnaround times for the pathologist and the patient.
The dramatic increase of computer power over the past decades, together with the development of advanced image analysis algorithms, has allowed the development of computer-assisted approaches capable of analyzing the bio-medical data and assisting in the diagnosis. Interpreting tissue slides manually is labor intensive, costly and involves the risk of human errors and inconsistency, while using automated image analysis can provide additional automatic, fast and reproducible analyses, assisting the pathologist in making an accurate and timely diagnosis.
Challenges remain in computer-assisted diagnosis, including increasing the accuracy and speed in providing a useful outcome, and at the same time handling the enormous amount of data involved in digital histological samples. Thus, while advancements have been made, there remains the need to further improve upon image acquisition and to balance image quality with speed in image acquisition. Indeed, properly focused images having sharp, discernible features are needed for further downstream processing, and failure to provide quality, focused images could lead to errors or ambiguous results. To date, however, only generic algorithms have been developed to determine image focus. For example, previous approaches have derived sharpness metrics based solely on a green channel of a color image. These generic approaches are not, however, able to consistently capture an image that provides both good focus and clear discrimination between differently colored features of an image, both indispensable qualities for images undergoing cellular based scoring. It would be desirable to have a new focus metric to help select the most suitable focus depth of a region of a tissue sample for further scanning and downstream processing. It is to be noted that for Dual ISH, since the gene expression is manifested through dots, the scanning needs is performed at 40× resolution, while for most digital pathology applications, a resolution of 20×0 is sufficient. Since a scanning resolution of 40× resolution is necessary for Dual ISH, an improved focus metric which ensures better quality at the 40× resolution is required for Dual ISH.
In addition, automatic quality evaluation of a whole slide scan has been another challenging problem, and there are no known state-of-the-art methods which can automatically detect “better quality” and “easy-to-score” regions, especially for Dual ISH scans. Thus, it would also be desirable to have an automated and computationally efficient way to assist a medical professional in assessing the quality of digital images of tissue samples, wherein the assessment accommodates different features appearing in the whole slide scanned image.